wolffd@0: % ---
wolffd@0: % Mother of allMTT Audio Features
wolffd@0: % ---
wolffd@0: 
wolffd@0: classdef MTTAudioFeature < handle
wolffd@0:     
wolffd@0:     % common properties
wolffd@0:     properties (Dependent)
wolffd@0:         
wolffd@0:         data;
wolffd@0:     end
wolffd@0:     
wolffd@0:     properties (Hidden)
wolffd@0:         
wolffd@0:         % ---
wolffd@0:         % TODO: get clip features by id and not by pos
wolffd@0:         % ---
wolffd@0:         
wolffd@0:         % position in db
wolffd@0:         db_pos;
wolffd@0:     end
wolffd@0:     
wolffd@0:     % do not save whole db into mat file
wolffd@0:     properties (Hidden, Transient)
wolffd@0:         
wolffd@0:         % database
wolffd@0:         my_db;
wolffd@0:     end
wolffd@0:     
wolffd@0:     
wolffd@0:     % common methods
wolffd@0:     methods 
wolffd@0:         
wolffd@0:         % ---
wolffd@0:         % constructor: pointer to feature in database
wolffd@0:         % ---
wolffd@0:         function feature = MTTAudioFeature(db, varargin)
wolffd@0:         % feature = MTTAudioFeatureBasicSm(db, varargin)
wolffd@0:      
wolffd@0:             if nargin >= 1
wolffd@0:                 % save database handle;
wolffd@0:                 feature.my_db = db;
wolffd@0:                 
wolffd@0:                 if nargin >= 2 
wolffd@0:                     if isnumeric(varargin{1})
wolffd@0:                         
wolffd@0:                         feature.db_pos = varargin{1};
wolffd@0: 
wolffd@0:                         % ---
wolffd@0:                         % read parameters from data, which should not be
wolffd@0:                         % overwritten by the manual imputs ?
wolffd@0:                         % ---
wolffd@0:                         feature.set_params(feature.data.info.params);
wolffd@0:                         
wolffd@0:                         if numel(varargin) > 1
wolffd@0:                             warning('Specified parameters cant be applied with preexisting data');
wolffd@0:                         end
wolffd@0: 
wolffd@0:                     else
wolffd@0:                         
wolffd@0:                         % set parameters for feature extraction
wolffd@0:                         feature.set_params(varargin{:});
wolffd@0:                     end
wolffd@0:                 end
wolffd@0:             
wolffd@0:             else
wolffd@0:                 % ---
wolffd@0:                 % TODO: empty constructor
wolffd@0:                 % ---
wolffd@0:             end
wolffd@0:         end
wolffd@0:         
wolffd@0:         % ---
wolffd@0:         % get and set methods, as the lazy matlab referencing
wolffd@0:         % is of no use when the feature has to be adjusted 
wolffd@0:         % during the progess of finalising
wolffd@0:         % ---
wolffd@0:         function data = get.data(feature)
wolffd@0:             
wolffd@0:             data = feature.my_db.featuredb(feature.db_pos);
wolffd@0:         end
wolffd@0:         
wolffd@0:         function set.data(feature, data)
wolffd@0:             
wolffd@0:              feature.my_db.featuredb(feature.db_pos) = data;
wolffd@0:         end
wolffd@0:         
wolffd@0:         function id = owner_id(feature)
wolffd@0:         % returns associated clip(s)
wolffd@0:         
wolffd@0:             for i = 1:numel(feature)
wolffd@0:                 id(i) = feature(i).data.info.owner_id;
wolffd@0:             end
wolffd@0:         end
wolffd@0:         
wolffd@0:         function out = dim(feature)
wolffd@0:         % returns dimension of single feature vector
wolffd@0:         
wolffd@0:             out = feature(1).data.final.dim;
wolffd@0:         end
wolffd@0:         
wolffd@0:         function label = labels(features)
wolffd@0:            label = [];
wolffd@0:             if isfield(features(1).data.final, 'vector_info')
wolffd@0:                 
wolffd@0:                 % ---
wolffd@0:                 % TODO: these labels should be stored at a central point,
wolffd@0:                 % as this is a big waste of memory
wolffd@0:                 % ---
wolffd@0:                 label = features(1).data.final.vector_info.labels;
wolffd@0:             end 
wolffd@0:         end
wolffd@0:         
wolffd@0:         function out = vector(features)
wolffd@0:         % returns the feature vector(s) 
wolffd@0:         % if multiple features are input, the vectors are 
wolffd@0:         % concatenated to a single matrix of size 
wolffd@0:         %       (feature.dim x numel(features)
wolffd@0:         
wolffd@0:         % finalise features if not done yet
wolffd@0:         if ~isfield(features(1).data, 'final') || features(1).data.final.dim == 0
wolffd@0:             
wolffd@0:             features.finalise();
wolffd@0:         end
wolffd@0:         
wolffd@0:         %shortcut for empty features
wolffd@0:         if features(1).data.final.dim < 1
wolffd@0:             out =[];
wolffd@0:             return
wolffd@0:         end
wolffd@0: 
wolffd@0:         out = zeros(features(1).data.final.dim, numel(features));
wolffd@0:         for i = 1:numel(features)
wolffd@0: 
wolffd@0:             % finalise single feature vectors
wolffd@0:             if ~isfield(features(i).data, 'final') || features(i).data.final.dim == 0
wolffd@0: 
wolffd@0:                 features(i).finalise();
wolffd@0:             end
wolffd@0: 
wolffd@0:             out(:,i) = features(i).data.final.vector;
wolffd@0:         end
wolffd@0:         end
wolffd@0:         
wolffd@0:         function out = common(feature)
wolffd@0:         % returns common feature values and params
wolffd@0:         
wolffd@0:            out = feature(1).my_db.commondb;
wolffd@0:         end
wolffd@0:         
wolffd@0:         % visualises all the finalised feature vectors at once
wolffd@0:         function a1 = visualise_vectors(features)
wolffd@0:             
wolffd@0:             % Collect source description data
wolffd@0:             ids = zeros( numel( features, 1));
wolffd@0:             
wolffd@0:             for i = 1: numel(features)
wolffd@0:                 
wolffd@0:                 ids(i) = features(i).owner_id();
wolffd@0:             end
wolffd@0: %             clips = MTTClip(ids);
wolffd@0:             
wolffd@0:             % get collective feature data
wolffd@0:             vec = features.vector();
wolffd@0:             
wolffd@0:             % feature description data
wolffd@0:             labels = features(1).labels;
wolffd@0:             
wolffd@0:             % plot data
wolffd@0:             h = figure;
wolffd@0:             imagesc(vec);
wolffd@0:             a1 = gca();
wolffd@0:             axis xy;
wolffd@0:             
wolffd@0:             set(a1,'XTick',1:numel(features), 'XTickLabel', ids);
wolffd@0:             
wolffd@0:             if ~isempty(labels)
wolffd@0:                 set(a1,'YTick', [1:features(1).data.final.dim], 'YTickLabel', labels);
wolffd@0:             end
wolffd@0:             
wolffd@0:             xlabel('Clip ID');
wolffd@0:         end
wolffd@0:         
wolffd@0:         
wolffd@0:         % ---
wolffd@0:         % compares the params of the feature with the 
wolffd@0:         % provided param struct or feature
wolffd@0:         % ---
wolffd@0:         function out = eq_params(this, in)
wolffd@0:         % function out = eq_params(this, in)
wolffd@0:         % 
wolffd@0:         % resolves if a feature with params(in) would be
wolffd@0:         % the same as the  given feature
wolffd@0:             
wolffd@0:             type = this.my_db.featuredb_type;
wolffd@0:             
wolffd@0:             % ---
wolffd@0:             % construct dummy feature to get the params parsing right
wolffd@0:             % ---
wolffd@0:             if isstruct(in)
wolffd@0:                 
wolffd@0:                 % call constructor for this feature 
wolffd@0:                 % type without valid db
wolffd@0:                 in = feval(type, 0, in);
wolffd@0:             end
wolffd@0:             
wolffd@0:             % return whether the strings are equal or not 
wolffd@0:             out = strcmp(this.param_hash(), in.param_hash());
wolffd@0:         end
wolffd@0:         
wolffd@0:         function unused = set_params(this, varargin)
wolffd@0:         % copies the parameters within the struct to the featrue instance,
wolffd@0:         % or
wolffd@0:         % uses the process_options function to set the parameters.
wolffd@0:         % this is used for initialisation / constructor of features
wolffd@0: 
wolffd@0:         unused = {};
wolffd@0:         if numel(this) > 1
wolffd@0:             
wolffd@0:             for i = 1:numel(this)
wolffd@0:                 set_params(this(i), varargin{:});
wolffd@0:             end
wolffd@0:         else
wolffd@0:             
wolffd@0:             if isstruct(varargin{1})
wolffd@0: 
wolffd@0:                 % ok, just copy the information
wolffd@0:                 % this.my_params = varargin{1};
wolffd@0: 
wolffd@0:                 % ---
wolffd@0:                 % NOTE: this is a compability script
wolffd@0:                 % set fields succesively to keep new / nonset field names
wolffd@0:                 % we do not add parameters!!
wolffd@0:                 % ---
wolffd@0:                 fields = fieldnames(varargin{1});
wolffd@0:                 for i = 1:numel(fields)
wolffd@0:                     
wolffd@0:                     % test whether the parameter is supported
wolffd@0:                     if isfield(this.my_params, fields{i})
wolffd@0:                         
wolffd@0:                         this.my_params.(fields{i}) = varargin{1}.(fields{i});
wolffd@0:                     end
wolffd@0:                 end
wolffd@0:             else
wolffd@0: 
wolffd@0:                 % get all parameter lines
wolffd@0:                 fields = fieldnames(this.my_params);
wolffd@0: 
wolffd@0:                 outputstring = '';
wolffd@0:                 inputstring = '';
wolffd@0: 
wolffd@0:                 % we collect the string for all the fields
wolffd@0:                 for i = 1:numel(fields)
wolffd@0: 
wolffd@0:                     % generate left- hand side of param collection
wolffd@0:                     outputstring = sprintf('%s this.my_params.%s',...
wolffd@0:                         outputstring, fields{i});
wolffd@0: 
wolffd@0:                     % right-hand-side
wolffd@0:                     inputstring = sprintf('%s ''%s'', this.my_params.%s',...
wolffd@0:                         inputstring, fields{i}, fields{i});
wolffd@0: 
wolffd@0:                     if i < numel(fields)
wolffd@0: 
wolffd@0:                         % put comma behind last argument
wolffd@0:                         inputstring = sprintf('%s,',inputstring);
wolffd@0:                         outputstring = sprintf('%s,',outputstring);
wolffd@0:                     end
wolffd@0: 
wolffd@0:                 end
wolffd@0: 
wolffd@0:                 % evaluate set
wolffd@0:                 eval(sprintf('[%s, unused] = process_options(varargin, %s);', ...
wolffd@0:                     outputstring, inputstring));
wolffd@0:             end
wolffd@0:         end
wolffd@0:         end %fun
wolffd@0:         
wolffd@0:         % ---
wolffd@0:         % saveto function 
wolffd@0:         % ---
wolffd@0:         function saveto(features, matfile)
wolffd@0:         % saves (multiple features to a .mat file)
wolffd@0:         
wolffd@0:             % get clip ids
wolffd@0:             c = zeros(numel(features), 1);
wolffd@0:             for i = 1:numel(features)
wolffd@0:                 c(i) = features(i).owner_id();
wolffd@0:             end
wolffd@0:         
wolffd@0:             % build clips
wolffd@0:             clips = MTTClip(c);
wolffd@0:             
wolffd@0:             % let db export the corresponding clips
wolffd@0:             features(1).my_db.export(matfile, clips);
wolffd@0:         end
wolffd@0:         
wolffd@0:         % ---
wolffd@0:         % destructor: do we really want to remove this 
wolffd@0:         % from the database? No, but 
wolffd@0:         % TODO: create marker for unused objects in db, and a cleanup
wolffd@0:         %  function
wolffd@0:         % ---
wolffd@0:         function delete(feature)
wolffd@0:             
wolffd@0:         end
wolffd@0:     end
wolffd@0:     
wolffd@0:     methods (Hidden = true)
wolffd@0:         
wolffd@0:         function assign(feature, db_pos)
wolffd@0:         % sets the feature data link
wolffd@0:         
wolffd@0:             feature.db_pos = db_pos;
wolffd@0:         end
wolffd@0:     end
wolffd@0:     
wolffd@0:     methods (Static)
wolffd@0:         
wolffd@0:         function ph = param_hash(type, varargin)
wolffd@0:         % loads the params for a feature type and adds the 
wolffd@0:         % given parameter values to it.
wolffd@0:         
wolffd@0:             % this function can be static or dynamic
wolffd@0:             if nargin > 1
wolffd@0:                 % static case
wolffd@0:                 dummy = feval(type,[], varargin{:});
wolffd@0:             else
wolffd@0:                 % dynamic case
wolffd@0:                 dummy = type;
wolffd@0:             end
wolffd@0:          ph = hash(xml_format(dummy.my_params),'MD5');
wolffd@0:         end
wolffd@0:         
wolffd@0:         function params = inherited_params(type, varargin)
wolffd@0:         % loads the params for a feature type and adds the 
wolffd@0:         % given parameter values to it.
wolffd@0:             
wolffd@0:             dummy = feval(type);
wolffd@0:             
wolffd@0:             params = dummy.my_params;
wolffd@0:             
wolffd@0:             % basic check if the input is correct
wolffd@0:             if mod(numel(varargin), 2) ~= 0
wolffd@0:                 error('number of params does not match number of values');
wolffd@0:             end
wolffd@0:             
wolffd@0:             % add the fields to the struct
wolffd@0:             for i = 1:2:(numel(varargin)-1);
wolffd@0:                 
wolffd@0:                 params.(varargin{i}) = varargin{i+1};  
wolffd@0:             end
wolffd@0:         end
wolffd@0:     end
wolffd@0: end
wolffd@0:     
wolffd@0:     
wolffd@0:     
wolffd@0:     
wolffd@0:     
wolffd@0:     
wolffd@0: